Data analysis accelerates medical diagnoses
Currently, new ways of using Big Data and Artificial Intelligence are emerging, the newest being undoubtedly the one that applies these technologies for the diagnosis and treatment of different diseases.
Being able to detect other diseases in time is a huge step towards effective treatment. Current algorithms allow us to establish patterns to predict something as complex as diseases.
For example, we can analyze the data provided by brain images from MRIs, with automatic learning algorithms. In this way we can anticipate and predict future cases, analyzing the behavior of the patient himself in real time.
Artificial Intelligence applied to the medical sector
All kinds of information can be monitored, from anxiety levels, heart rate, amount of exercise a person does, quality of sleep.
To give another example, data robotics is able to learn, interpret, and also recognize behavioral cues of children with autism. Technology can predict their moods and establish patterns for maintaining contact with them. This technology is currently being tested for integration into voice assistants for people with autism.
Structured or unstructured data
You should know that a lot of data can be handled in a structured or unstructured way. This is a special complication for its management. To do this, you will need technologies that allow you to manage all types of data and then have the ability to analyze them.
The importance of analyzing consolidated data
This will undoubtedly be one of the main challenges for data analysis in the health sector. All kinds of data are collected and handled. Some are easy to handle, analyse and search, and others are not so easy. Currently it is estimated that only 20% of the data is structured. The rest cannot be sorted by rows and columns (nor do they have an associated data model).
In the case of the health sector, we are talking about data ranging from photos, video/audio files, text, pdfs… In other words, there is an enormous variety of records that can be used. And that is precisely where artificial intelligence and automatic learning come in.
The ability to be able to relate three types of data will be crucial:
- Structured data.
- Semi-structured data.
- Unstructured data.
Allowing conclusions to be drawn from it. Without a doubt, Artificial Intelligence and Big Data are crucial to optimize the processes at this point since it gives value and intelligence to the data in order to draw conclusions from them.
One of the big risks companies face is data inconsistency, which is estimated to be present in 50% of companies. This undoubtedly makes advanced analytical processes very difficult.
